groundanything-vlm / data /tasks.json
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Deploy GroundAnything-VLM frontend with shared ZeroGPU backend
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{
"routes": {
"grounding": [
"Grounding",
"Open-vocabulary object localization"
],
"dense": [
"Dense",
"Dense instance localization"
],
"referring": [
"Referring",
"Language-guided referring"
],
"dense_point": [
"Dense Point",
"Dense point prediction"
],
"referring_point_in_mask": [
"Referring Point in Mask",
"Point inside a referred target"
],
"dense_point_in_mask": [
"Dense Point in Mask",
"Point inside multiple targets"
],
"visual_prompt": [
"Visual Prompt",
"Exemplar-guided localization"
],
"ocr": [
"OCR",
"Text recognition and localization"
],
"gui": [
"GUI",
"Interface element grounding"
]
},
"help": {
"grounding": [
"Open-Vocabulary Grounding",
"Turn category names into visual primitives: what is present, and where it is.",
"Separate categories with commas. Select a result to inspect its original pixels.",
"car, person"
],
"dense": [
"Grounding in Dense Scenes",
"Explore object-level perception in crowded scenes, including small and overlapping instances.",
"Enter object categories. Inspect overlapping predictions one instance at a time.",
"person, chair"
],
"referring": [
"Language, Grounded in Context",
"Link descriptions of appearance, position, and relationships to a specific visual target.",
"Describe appearance, position, or relationships in a complete phrase.",
"The person standing beside the table"
],
"dense_point": [
"Dense Object Pointing",
"Represent multiple objects as localized points: a compact form of visual grounding.",
"Describe the targets to locate. Points indicate positions, not object boundaries.",
"All visible people"
],
"referring_point_in_mask": [
"Point Inside a Referred Target",
"Use a description to predict a point inside the target object.",
"Describe the target. The output is an image-relative point inside the object.",
"The person wearing a flotation device"
],
"visual_prompt": [
"Grounding by Visual Example",
"Use spatial exemplars to identify related instances through a shared grounding interface.",
"Green INPUT boxes come from your prompt, not model predictions. Coordinates use the 0–999 range.",
"Given reference boxes <|box_start|><100><100><200><200><|box_end|> ..."
],
"ocr": [
"Reading with Spatial Context",
"Bind recognized text to its image region, connecting what is read with where it appears.",
"Use an OCR instruction. Select a transcription to inspect the original pixels.",
"Read and locate the text in the image"
],
"dense_point_in_mask": [
"Point Inside Multiple Targets",
"Predict an interior point for each matching instance in a crowded scene.",
"Separate categories with commas. Each prediction marks a point inside an instance.",
"van, bus, truck, car, pedestrian"
],
"gui": [
"Grounding Intent in Interfaces",
"Map an interaction instruction to a visual target within an interface.",
"Describe the element to select. The demo predicts a point; it does not execute clicks.",
"Click the search button"
]
},
"prefixes": {
"grounding": "Locate all the instances that match the following categories: ",
"dense": "Locate all the instances that match the following categories: ",
"referring": "Locate the target referred to by the following description: ",
"dense_point": "Point to: ",
"refer_point": "Point to the target referred to by the following description: ",
"referring_point_in_mask": "Point to the target referred to by the following description: ",
"dense_point_in_mask": "Point to: ",
"layout": "Detect all document layout elements that match the following categories: ",
"gui": "Point to the UI element to click for the following instruction: "
},
"categoryRoutes": [
"dense",
"dense_point_in_mask",
"grounding",
"layout"
]
}